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The NIG-S&ARCH model: a fat-tailed, stochastic, and autoregressive conditional heteroskedastic volatility model

Morten Jensen and Asger Lunde ()

Econometrics Journal, 2001, vol. 4, issue 2, 10

Abstract: This paper examines the capabilities of the Normal Inverse Gaussian distribu-tion as a model for stock returns. We extend the model of Barndorff-Nielsen (1997) to allow for a richer volatility structure and compare with the existing GARCH-type models. We conclude that the proposed model outperforms some of the most praised GARCH-M models. In particular, we make a big gain in modelling the skewness of equity returns.

Keywords: Normal Inverse Gaussian distribution; Observation driven model; Nonlinear state space model; Filtering. (search for similar items in EconPapers)
Date: 2001
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Econometrics Journal is currently edited by Richard J. Smith, Oliver Linton, Pierre Perron, Jaap Abbring and Marius Ooms

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